# Replication Data for 'The Evolution of Monitoring: Evidence from Text Analysis of Election Monitoring Reports'

This folder contains the corpus data and Python code used in the analyses reported in our article, 'The Evolution of Monitoring: Evidence from Text Analysis of Election Monitoring Reports.'

- `reports_1995_2020.tsv` (tab-separated; utf-8): Contains information on all the election monitoring reports we collected for the period of 1995-2020, including the main text for each report.
- `preprocessed_corpus_stemmed.csv` (comma-separated; utf-8): Contains the preprocessed texts from the collected monitoring reports, along with relevant pieces of information. Each row corresponds to each of the paragraphs comprising the monitoring reports. Each text was subjected to a series of standard preprocessing procedures, including stemming.
- `count.ipynb` (Jupyter Notebook): Contains Python code for replicating the word frequency analysis reported in our article.
- `LDA.ipynb` (Jupyter Notebook): Contains Python code for replicating the topic analysis using Latent Dirichlet Allocation (LDA).

**Note**: Ensure that you have the necessary Python libraries and dependencies installed before running the Jupyter Notebook files.
